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Attacking contrast enhancement forensics in digital images

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Science China(Information Sciences) 2014年第5期57卷 170-182页

作者： CAO Gang ZHAO Yao NI RongRong TIAN HuaWei YU LiFang School of Computer Science Communication University of China Institute of Information Science Beijing Jiaotong University People's Public Security University of China

Currently,plenty of digital image forensic techniques have been proposed and used as diagnostic *** is urgent and significant to assess the reliability of such techniques applied in practical *** this paper,we investigate the security of existing digital image contrast enhancement(CE)forensic *** the standpoint of attackers,we propose two types of attacks,CE trace hiding attack and CE trace forging attack,which could invalidate the forensic detector and fabricate two types of forensic errors,*** CE trace hiding attack is implemented by integrating local random dithering into the design of pixel value *** CE trace forging attack is proposed by modifying the gray level histogram of a target pixel region to counterfeit peak/gap *** trace forging attack is typically applied to create sophisticated composite images which could deceive the prior CE-based composition *** experimental results demonstrate the efficacy of our proposed CE anti-forensic schemes.

关键词： digital forensics anti-forensics attack contrast enhancement composite image histogram

A New Method of CT Medical Images contrast enhancement

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Chinese Journal of Biomedical Engineering(English Edition) 2004年第1期13卷 28-38页

作者： SUNFeng-rong LIUWei WANGChang-yu MEILiang-mo SchoolofInformationScienceandEngineering ShandongUniversity.Jinan250100

A new method of contrast enhancement is proposed in the paper using multiscale edge representation of images, and is applied to the field of CT medical image processing. Comparing to the traditional Window technique, our method is adaptive and meets the demand of radiology clinics more better. The clinical experiment results show the practicality and the potential applied value of our method in the field of CT medical images contrast enhancement.

关键词： contrast enhancement Dyadic wavelet transform Multiscale edge representation Computed tomography

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Adaptive Local contrast enhancement of High Dynamic Range Image

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Adaptive Local Contrast Enhancement of High Dynamic Range Im...

Recursive Plateau Histogram Equalization for the contrast enhancement of the Infrared Images

2009 9th International Conference on Electronic Measurement & Instruments（ICEMI’2009）

作者： Linan Jiao1 Zhaoyun Sun1 Aimin Sha2 Juan Zhang1 1 College of Information Engineering Chang’an University 2 College of Highway Chang’an University Middle Section of Ring Road 2 South 710064 Xi’an China

Most existing global contrast enhancement algorithm can not deal with high dynamic range images. Thus a simplified logarithmic transformation equation has been proposed in this paper. A partially overlapped sub-block method is also adopted to perform local contrast enhancement. For purpose of optimization, two contrast measures are used for finding optimal transformation parameters. They merge into a new algorithm, called POSLT （Partially Overlapped Sub-block Logarithmic transformation）. POSLT exhibits good performance and Controllability even if it has high computational complexity. Our experimental results give firmly support of POSLT.

关键词： contrast enhancement High Dynamic Range Image logarithmic transformation contrast Measure Subblock.

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Recursive Plateau Histogram Equalization for the Contrast En...

Reversible Data Hiding with contrast enhancement Using Bi-histogram Shifting and Image Adjustment for Color Images

2010 3rd International Conference on Computer and Electrical Engineering(ICCEE 2010)

作者： Zongwei Lu Zhide Tang Lin Zhou Hao Yang Lisen Lin State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University

One simple and efficient algorithm based on recursive plateau histogram equalization for the contrast enhancement of the infrared images is proposed in this paper. In this method, the plateau threshold is selected automatically as the average value of the probability density function. Based on the threshold value, the probability density function is divided into two sub-groups. The sub-group whose values are greater than the threshold value is clipped. New threshold value is calculated for another sub-group whose values are less than the old threshold value and the separation process is performed recursively on it. Experimental results show that our method can enhance the contrast of the infrared images better than other histogram equalization based methods. Furthermore, our method is simple enough to make it suitable to be implemented by FPGA for real time image process.

关键词： contrast enhancement Histogram equalization Plateau histogram equalization Image enhancement

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Journal of Quantum Computing 2022年第3期4卷 183-197页

作者： Goma Tshivetta Christian Fersein Jorvialom Lord Amoah Engineering Research Center of Digital Forensics Ministry of EducationNanjing University of Information Science&TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China

Prior versions of reversible data hiding with contrast enhancement(RDHCE)algorithms strongly focused on enhancing the contrast of grayscale ***,RDHCE has recently witnessed a rise in contrast enhance-ment algorithms concentrating on color *** paper implies a method for color images that uses the RGB(red,green,and blue)color model and is based on bi-histogram shifting and image ***-histogram shifting is used to embed data and image adjustment to achieve contrast enhancement by adjusting the images resulting from each channel of the color images before combining them to generate the final enhanced *** are first divided into three channels-R,G,and B-and the Max,Med,and Min channels are then determined from *** histogram shifting,some calculations are done to determine how many iterations there will be for each *** images are adjusted to improve visual quality in the enhanced images after data has been embedded in each *** experimental results show that the enhanced images produced by the proposed method are qualitatively and aesthetically superior to those produced by some earlier methods,and their quality was assessed using PSNR,SSIM,RCE,RMBE,and *** embedding rate obtained by the suggested method is acceptable.

关键词： contrast enhancement bi-histogram shifting image adjustment

A Bi-Histogram Shifting contrast enhancement for Color Images

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Journal of Quantum Computing 2021年第2期3卷 65-77页

作者： Lord Amoah Ampofo Twumasi Kwabena Engineering Research Center of Digital Forensics Ministry of EducationNanjing University of Information Science&TechnologyNanjing210044China School of Computer and Software Nanjing University of Information Science&TechnologyNanjing210044China Department of Computer Science University of Ghana-LegonAccra00233Ghana

Recent contrast enhancement(CE)methods,with a few exceptions,predominantly focus on enhancing gray-scale *** paper proposes a bi-histogram shifting contrast enhancement for color images based on the RGB(red,green,and blue)color *** proposed method selects the two highest bins and two lowest bins from the image histogram,performs an equalized number of bidirectional histogram shifting repetitions on each RGB channel while embedding secret data into marked *** proposed method simultaneously performs both right histogram shifting(RHS)and left histogram shifting(LHS)in each histogram shifting repetition to embed and split the highest bins while combining the lowest bins with their neighbors to achieve histogram equalization(HE).The least maximum number of histograms shifting repetitions among the three RGB channels is used as the default number of histograms shifting repetitions performed to enhance original *** to an existing contrast enhancement method for color images and evaluated with PSNR,SSIM,RCE,and RMBE quality assessment metrics,the experimental results show that the proposed method's enhanced images are visually and qualitatively superior with a more evenly distributed *** proposed method achieves higher embedding capacities and embedding rates in all images,with an average increase in embedding capacity of 52.1%.

关键词： contrast enhancement bi-histogram shifting histogram equalization

A Novel Approach for enhancement of Geometric and contrast Resolution Properties of Low contrast Images

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IEEE/CAA Journal of Automatica Sinica 2018年第2期5卷 628-638页

作者： Koushlendra Kumar Singh Manish Kumar Bajpai Rajesh Kumar Pandey Department of Computer Science and Engineering National Institute of Technology Jamshedpur 831014 India Indian Institute of Information Technology Design & Manufacturing Jabalpur MP 482005 India Department of Mathematical Sciences In- dian Institute of Technology Varanasi U.P. 221005 India

The present work encompasses a new image enhancement algorithm using newly constructed Chebyshev fractional order differentiator. We have used Chebyshev polynomials to design Chebyshev fractional order differentiator. We have generated the high pass filter corresponding to it. The designed filters are applied for decomposing the input image into four bands and low-low(L-L) sub-band is updated using correction coefficients. Reconstructed image with updated L-L sub-band provides the enhanced image. The visual results obtained are encouraging for image enhancement. The applicability of the developed algorithm is illustrated on three different test *** effects of order of differentiation on the edges of images have also been presented and discussed.

关键词： Index Terms-Chebyshev polynomial based approximation contrast enhancement fractional order differentiator.

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An Artificial Intelligence-Based Framework for Fruits Disease Recognition Using Deep Learning

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Computer Systems Science & Engineering 2024年第2期48卷 529-554页

作者： Irfan Haider Muhammad Attique Khan Muhammad Nazir Taerang Kim Jae-Hyuk Cha Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science Hanyang UniversitySeoulKorea

Fruit infections have an impact on both the yield and the quality of the *** a result,an automated recognition system for fruit leaf diseases is *** artificial intelligence(AI)applications,especially in agriculture,deep learning shows promising disease detection and classification *** recent AI-based techniques have a few challenges for fruit disease recognition,such as low-resolution images,small datasets for learning models,and irrelevant feature *** work proposed a new fruit leaf leaf leaf disease recognition framework using deep learning features and improved pathfinder *** fruit types have been employed in this work for the validation process,such as apple,grape,and *** the first step,a noisy dataset is prepared by employing the original images to learn the designed framework *** EfficientNet-B0 deep model is fine-tuned on the next step and trained separately on the original and noisy *** that,features are fused using a serial concatenation approach that is later optimized in the next step using an improved Path Finder Algorithm(PFA).This algorithm aims to select the best features based on the fitness score and ignore redundant *** selected features are finally classified using machine learning classifiers such as Medium Neural Network,Wide Neural Network,and Support Vector *** experimental process was conducted on each fruit dataset separately and obtained an accuracy of 100%,99.7%,99.7%,and 93.4%for apple,grape,Citrus fruit,and citrus plant leaves,respectively.A detailed analysis is conducted and also compared with the recent techniques,and the proposed framework shows improved accuracy.

关键词： Fruit disease contrast enhancement augmentation deep learning fusion feature selection classification

A Post-Processing Algorithm for Boosting contrast of MRI Images

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Computers, Materials & Continua 2022年第8期72卷 2749-2763页

作者： B.Priestly Shan O.Jeba Shiney Sharzeel Saleem V.Rajinikanth Atef Zaguia Dilbag Singh Department of Electronics&Communication Engineering Chandigarh UniversityMohali140413India Department of Electrical Electronics&Communication EngineeringGalgotias UniversityGreater Noida201310India Department of Electronics and Instrumentation Engineering St.Joseph’s College of EngineeringChennai600119Tamil NaduIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of Electrical Engineering and Computer Science Gwangju Institute of Science and TechnologyGwangju61005Korea

Low contrast of Magnetic Resonance(MR)images limits the visibility of subtle structures and adversely affects the outcome of both subjective and automated ***-of-the-art contrast boosting techniques intolerably alter inherent features of MR *** changes in brightness features,induced by post-processing are not appreciated in medical imaging as the grey level values have certain diagnostic *** overcome these issues this paper proposes an algorithm that enhance the contrast of MR images while preserving the underlying features as *** method termed as Power-law and Logarithmic Modification-based Histogram Equalization(PLMHE)partitions the histogram of the image into two sub histograms after a power-law transformation and a log *** a modification intended for improving the dispersion of the sub-histograms and subsequent normalization,cumulative histograms are *** grey level values are computed from the resultant cumulative *** performance of the PLMHE algorithm is comparedwith traditional histogram equalization based algorithms and it has been observed from the results that PLMHE can boost the image contrast without causing dynamic range compression,a significant change in mean brightness,and contrast-overshoot.

关键词： contrast enhancement histogram equalisation image quality magnetic resonance imaging medical image analysis post-processing